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Practical Statistics for Data Scientists

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic;

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Statistical Foundations, Reasoning and Inference

and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the;

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Applied Statistics for Environmental Science with R

science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and;

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Statistics for Data Scientists

often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical;

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Essential Statistics for Non-STEM Data Analysts

Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data;

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Easy Statistics for Food Science with R

of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods;

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Statistical Foundations of Data Science

Provides theoretical insights and justification of the statistical procedures for the analysis of high-dimensional data Presents a general;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Secrets of Statistical Data Analysis and Management Science!

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Statistical Methods for Materials Science: The Data Science of Microstructure Characterization

Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for;

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Mathematical Problems in Data Science

and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets;

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Numeric Data Services and Sources for the General Reference Librarian

The proliferation of online access to social science statistical and numeric data sources, such as the U.S. Census Bureau's American Fact;

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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Computer Age Statistical Inference

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data;

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Stock Price Analysis Through Statistical And Data Science Tools: an Overview

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Handbook of Neuroimaging Data Analysis

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development;

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Introduction to Statistical and Machine Learning Methods for Data Science

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Introduction to Statistical and Machine Learning Methods for Data Science

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Essentials of Data Science and Analytics

, data science uses visualization techniques using specially designed big data software and statistical programming language, such as R;

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Computer Age Statistical Inference, Student Edition

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and;

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Statistical Methods for Materials Science

Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for;

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Practical Data Science With R

of all levels. RETAIL SELLING POINTS Demonstrations of need-to-know statistical ideas Covers all aspects of the project lifecycle Data science;

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Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques

in data analysis, survival data analysis and survival models for cancer patients, statistical analysis and neural network techniques for genomic;

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Doing Data Science in R

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry;

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Statistical Data Science

As an emerging discipline, data science broadly means different things across different areas. Exploring the relationship of data science;

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Univariate Bivariate & Multivariate Stat

A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate;

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